127 citations · 434 across the 18 of their papers we have counts for
4 papers · 1 filter
REFORMS: Reporting Standards for Machine Learning Based Science
Sayash Kapoor, Emily Cantrell, Kenny Peng +16
Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and ge…
DroidDissector: A Static and Dynamic Analysis Tool for Android Malware Detection
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
DroidDissector is an extraction tool for both static and dynamic features. The aim is to provide Android malware researchers and analysts with an integrated tool that can extract a…
Externally validating the IoTDevID device identification methodology using the CIC IoT 2022 Dataset
Kahraman Kostas, Mike Just, Michael A. Lones
In the era of rapid IoT device proliferation, recognizing, diagnosing, and securing these devices are crucial tasks. The IoTDevID method (IEEE Internet of Things 2022) proposes a m…
Reassessing feature-based Android malware detection in a contemporary context
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
We report the findings of a reimplementation of 18 foundational studies in feature-based machine learning for Android malware detection, published during the period 2013-2023. Thes…